LiPowerline: Point Cloud Processing Software for Power Line Inspection and Analysis LiDAR360 Suite Version 3.0 features LiPowerline, an industry specific solution for identifying, analyzing, and reporting hazards that impact powerline corridors. As a standalone software, LiPowerline provides those tasks with maintaining and operating electricity transmission and distribution assets with a packaged set of standard and advanced tools for classifying objects contained within in 3D point clouds and detecting vegetation that has grown to encroach upon user-defined powerline clearance zones under observed and simulated conditions. Users can also generate detailed clearance zone violation reports that include exact locations where hazard mitigation work needs to be carried out. Outputs generated from the software can be visualized in LiPowerline’s 3D view windows or exported to printable documents for delivery to vegetation mangers, utility foresters, and arborists who maintain grid reliability and public safety. With the incorporation of LiPowerline into its product ecosystem, GreenValley International provides fully integrated solutions for acquiring, processing, and analyzing point cloud datasets that enable utility managers to make timely and well-informed decisions. Figure 1. LiPowerline provides industry-specific point cloud processing software tools designed to support the inspection of electric grid assets and their surroundings. Routine inspection of powerline corridors to ensure clearance zones are sufficient and well maintained is a challenging mission critical operation that almost every mile of electricity grid infrastructure requires. LiDAR survey data can serve as an excellent source of accurate distance measurement information for powerline managers to have available as they seek to identify hazardous situations during inspection periods. In many situations, methods that have GreenValley International 1
Transcript
LiPowerline: Point Cloud Processing Software for Power Line Inspection and Analysis
LiDAR360 Suite Version 3.0 features LiPowerline, an industry specific solution for identifying, analyzing, and reporting hazards that impact powerline corridors. As a standalone software, LiPowerline provides those tasks with maintaining and operating electricity transmission and distribution assets with a packaged set of standard and advanced tools for classifying objects contained within in 3D point clouds and detecting vegetation that has grown to encroach upon user-defined powerline clearance zones under observed and simulated conditions. Users can also generate detailed clearance zone violation reports that include exact locations where hazard mitigation work needs to be carried out. Outputs generated from the software can be visualized in LiPowerline’s 3D view windows or exported to printable documents for delivery to vegetation mangers, utility foresters, and arborists who maintain grid reliability and public safety. With the incorporation of LiPowerline into its product ecosystem, GreenValley International provides fully integrated solutions for acquiring, processing, and analyzing point cloud datasets that enable utility managers to make timely and well-informed decisions.
Figure 1. LiPowerline provides industry-specific point cloud processing software tools designed to support the inspection of electric grid assets and their surroundings.
Routine inspection of powerline corridors to ensure clearance zones are sufficient and well maintained is a challenging mission critical operation that almost every mile of electricity grid infrastructure requires. LiDAR survey data can serve as an excellent source of accurate distance measurement information for powerline managers to have available as they seek to identify hazardous situations during inspection periods. In many situations, methods that have
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traditionally been used to detect powerline clearance zone violations prove to be very labor-intensive and time-consuming when compared to the results that can be generated from a well-planned and properly executed LiDAR-driven inspection process.
Model and Classify Powerline Infrastructure and Corridor Features LiDAR data provides detailed 3D models of physical structures that make up the electric grid as well the objects surrounding powerline infrastructure. Through its robust point cloud classification tools, LiPowerline allows users to easily separate data regions containing individual grid assets (e.g. conductors, towers, insulators, etc.) from those that represent potential hazards and sources of concern (e.g. encroaching vegetation, trees with threatening leans, bodies of water, etc.). Driven by state-of-the art machine learning algorithms, the classification functionality removes the need for tedious manual classification of point clouds and presents the opportunity to reduce data processing costs significantly.
Figure 2. LiPowerline’s classification tools leverage advanced machine-learning algorithms to partially automate the tedious process of identifying and labeling specific feature types contained within LiDAR point clouds including; conductors, shield wires, towers or structures, high, medium and low vegetation types, ground, buildings, and more.
Once classified, LiPowerline contains tools that convert 3D point cloud models of towers, cross arms, insulators, and conductors to polyline vector objects; which can then be exported as a shapefiles (*.shp) for future use or further analysis in third-party software programs.
Figure 3. Vectorized powerline model generated from 3D point cloud data.
Automatic Danger Point Detection After classifying and vectorizing input point cloud data, LiPowerline is able to automate the process of identifying areas where user-defined minimum clearance distance requirements are not met. The software labels data points that falling within the clearance zones as Danger Points. Danger Points most often represent encroaching vegetation but in some instances they may also
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belong to point cloud regions that document buildings, rail roads, or other features for which minimum separation distance thresholds must be maintained. The coordinate values for individual Danger Points detected are logged to an output table which can be easily edited during the QA\QC stages of data processing. Users can also choose to generate inspection reports containing the coordinates of Danger Point locations, measured distances between each Danger Point and the powerline object it is nearest to, as well as company or client specific pieces of information like contact details, project names, tower IDs, span numbers, and inspection dates. Danger Points can also be exported to .kml files and viewed outside of LiPowerline or other programs included in GreenValley's LiDAR360 Suite.
Figure 4. LiPowerline automates the detection of point cloud regions that violate user-defined minimum clearance distance requirements and labels them as Danger Points. Danger Point locations and clearances can then be visualized in LiPowerline’s 3D viewing window (in red) and are output as a list of coordinates values.
Simulate Impacts of Weather on Powerline Clearance Zones Powerline conductors and insulators respond to changes in temperature by expanding or contracting. Seasonal changes in temperature will impact the amount of sag and sway observed along a given span of powerline throughout the year. Warmer summer temperatures will cause sag and sway to increase while colder winter-time temperatures will generally decrease these properties of powerlines. When ice accumulates on the conductors and weighs them down sag and sway will increase. Thus, weather conditions can significantly impact the spatial extents of
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clearance zones that must be maintained throughout the year. LiPowerline allows users to simulate the amount of sag and sway present in a given span of infrastructure under specified temperatures, windspeeds, and ice loads.
Figure 5. Outputs of LiPowerline’s Comprehensive Working Simulation tools that allow users to evaluate how clearance zone extents will change under specified temperatures, wind speeds, and ice loads. The green lines represent the position of the conductors at the time of point cloud data capture while the cyan colored lines represent the position of the conductor under simulated winter time (upper) and summer time (lower) conditions.
Early Warning Analysis LiPowerline is capable of modeling future vegetation heights based on observed growth rates and estimating when clearance zone violations are likely to occur. This unique functionality provides utility foresters and vegetation managers with an important forecasting tool in areas where fast-growing tree species can be found. In addition to vegetative growth simulation, LiPowerline’s early warning analysis toolset allows users to identify individual trees that have potential to fall towards and damage powerline infrastructure if they were to topple over.
Figure 6. LiPowerline contains early warning analysis tools that allow users to simulate vegetation growth and identify individual trees that will encroach upon the clearance zone within a specified amount of time.
To trial LiPowerline please download LiDAR360 Suite and request a 30-day free trial. For more information and a free 30-day trial of our entire software suite please visit www.greenvalleyintl.com/software/software-downloads
